Intent-based lead generation finds prospects while they are actively shopping, not just when they fit your profile. Here are the signal types, a simple scoring model, and a weekly workflow.
Intent-based lead generation is the practice of finding and prioritizing prospects based on evidence that they are actively looking for a solution right now, rather than on whether they merely match your ideal customer profile. A static list tells you who could buy. An intent signal tells you who is shopping this week. This guide explains the signal types, how to score them, and a simple weekly workflow a small B2B team can run without an enterprise data contract.
Intent-based lead generation means building your pipeline from buying signals instead of from demographics alone. A buying signal is any observable action that suggests a person or company is researching, comparing or ready to purchase a solution in your category.
Traditional prospecting starts with filters: industry, headcount, job title. That gives you a list of companies that could buy. Intent-based prospecting adds a second question: which of them are showing behaviour that says they want to buy soon? Bombora, one of the larger intent data providers, defines intent data as signals showing when buyers are actively researching topics, based on the content they consume.
The practical difference shows up in your first message. With a static list you have to guess the problem. With a signal you already know it.
Buyer intent matters more because B2B buyers do most of their research before they ever talk to a vendor, and they usually make the first move themselves.
The 6sense 2025 B2B Buyer Experience Report found that buyers first engaged sellers roughly 61% of the way through their journey, and that 79% of those first interactions were started by the buyer. The same study found that buyers purchased from a vendor on their day-one shortlist 95% of the time. Gartner research adds that 75% of B2B buyers prefer a sales experience without a rep.
Put those together and the problem is clear. Most of the decision happens in a window you cannot see, and the shortlist forms early. Intent signals are how you get into that window while the shortlist is still open.
There are three main types of intent data: first-party signals from your own channels, third-party signals licensed from data providers, and public conversation signals from places like Reddit and LinkedIn.
| Signal type | Where it comes from | What it tells you | Main limitation |
|---|---|---|---|
| First-party | Your website, product trial, emails, events | Someone already knows you and is engaging | Only covers people who found you |
| Third-party | Data co-ops, publisher networks, bidstream | An account is researching a topic across the web | Usually account-level, rarely names the person or the exact problem |
| Public conversation | Reddit threads, LinkedIn posts, forums, review sites | A named person describing a problem or asking for a tool | Fast-moving and noisy, so it needs filtering |
First-party intent data is behaviour on channels you own or pay for: pricing page visits, demo requests, trial activity, webinar attendance and replies to your emails. It is the most reliable signal you have, but it only covers people who already found you.
Third-party intent data is research activity observed outside your own channels and sold by providers. It is useful for spotting accounts that are reading about your category. However, it typically tells you that a company is researching a topic, not which person is involved or what they are frustrated by.
Public conversation signals are posts where a real person states their need in the open. “Looking for an alternative to our current CRM, the per-seat price doubled” is a buying signal with a name, a reason and a deadline attached. These signals are the most explicit of the three, which is why they are often the easiest to act on well.
Score each signal on three factors, fit, freshness and explicitness, from 0 to 3 each, and only act on signals that total 6 or more out of 9.
We call this the FFE score. It is deliberately simple, so a founder or one sales rep can apply it in seconds.
Third-party topic surges tend to score high on fit but low on explicitness. Public posts often score high on explicitness and freshness, but you still need to check fit. Neither type wins on its own, which is why the score matters more than the source.
| Signal | Fit | Freshness | Explicitness | FFE score | Action |
|---|---|---|---|---|---|
| Reddit: founder asks for outbound help | 3 | 3 | 3 | 9/9 | Reply today |
| Third-party topic surge, no named contact | 3 | 2 | 1 | 6/9 | Research queue |
| LinkedIn opinion post | 1 | 1 | 1 | 3/9 | Skip |
Here is an illustrative scenario, not a customer case study. A five-person agency sells outbound setup services to seed-stage SaaS companies. On a Tuesday morning they review three signals.
The agency replies to the Reddit founder first, with a genuinely useful answer about warming domains and list hygiene, and mentions what they do in one sentence at the end. They add the surging account to a research list and look for the right contact. They skip the LinkedIn opinion post. Total time: about fifteen minutes, spent on the one conversation most likely to turn into a call.
Set it up in four steps: define the phrases buyers use, choose where to listen, score and route signals, then reply and follow up within a day.
List 10 to 20 phrases a frustrated buyer would type. Include competitor names (“alternative to X”), cost complaints (“X got too expensive”), and problem statements (“our reply rate is dead”). Avoid category jargon nobody says out loud.
Start with your own pricing page and demo form for first-party signals. Then add the communities where your buyers ask for advice. For many B2B products that means a handful of subreddits and LinkedIn. Our guide on how to find buying signals on Reddit covers the Reddit side in detail.
Apply the FFE score. Signals at 7 to 9 get a reply today. Signals at 6 go into a research queue. Anything below 6 is ignored. Consistency matters more than precision here.
Answer the question in the thread first, even when the best answer is not your product. Respect each community’s self-promotion rules. Then send a short, private follow-up that references what they wrote. Because you know their problem, the message can be three sentences long.
The most common mistakes are acting on stale signals, pitching instead of helping, and treating every mention of a keyword as purchase intent.
You can automate the listening and the first draft, but the judgement about whether and how to reply should stay with a person.
Manually checking several communities every day does not scale past a few hours a week. FindyLeads monitors Reddit and LinkedIn for buying signals that match your product, surfaces the relevant conversations, and drafts a reply you can edit before posting. The point is not to remove the human. It is to make sure the human spends their fifteen minutes on the right three threads.
Lead scoring ranks contacts you already have, usually based on fit and engagement with your own channels. Intent data adds evidence of active buying research, including from people who have never visited your site. Many teams feed intent signals into their lead score.
No. Third-party intent contracts are often priced for larger teams, but first-party signals and public conversation signals are available to any company. A founder can run a basic intent workflow in about thirty minutes a day.
Aim for the same day. Public requests for recommendations attract most of their replies early, and the buyer’s shortlist forms quickly. A useful reply within 24 hours is worth far more than a polished one a week later.
It depends on the community. Each subreddit sets its own rules, and many restrict self-promotion. Read the rules first, lead with a genuinely helpful answer, and disclose your affiliation if you mention your own product.
Reference what they wrote, answer their question or add one useful idea, and ask a small question back. Keep it to three or four sentences and do not attach a deck or ask for a meeting in the first message.
Intent-based lead generation works because it changes when you show up, not just who you contact. Buyers make most of the decision before they talk to anyone, so the advantage goes to teams that spot the signal early and reply with something useful. Start with a phrase list, listen in two or three places, score every signal, and reply the same day.
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